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Effects of Topography and Social Position on the Solar Radiation of Individual Trees on a Hillslope in Northwest China

Jiamei Li,P. Yu,Yan-Ping Wan,Yanhui Wang,Bingchen Liu,Yipeng Yu

Published 2023 in Forests

ABSTRACT

Solar radiation is a key factor influencing the photosynthesis and transpiration of trees. In mountainous regions, solar radiation income exhibits strong spatial heterogeneity due to topographical variations and the structural complexity of the forest. However, how the solar radiation income of individual trees in different social positions varies with slope position remains unclear. In this study, the daily solar radiation of the horizontal ground (Rh), different slope positions (i.e., at different locations on a hillslope, Rs) and individual trees with different social positions in the forest (Ri) were monitored from May to October in 2020 and 2021. The daily solar radiation income of a single hillslope (Rf) was applied to quantify the Rs response to the slope and aspect (i.e., slope effect) and the shade from the opposite mountain (i.e., shaded terrain effect). Our results showed that the Rf was 27.8% lower than Rh due to the slope effect of the sample slope. In the different slope positions, 2.7%–46.9% of solar radiation was lost due to the shaded terrain effect. A stronger limitation of Rs by the shaded terrain effect was detected on the bottom slope compared to that of the upper slope. The better the social position of an individual tree (i.e., tree dominance (Dom) and the distance between trees (D)), the more solar radiation it received, ranging from 22.4 to 95.3%. The dominant factor contributing to changes in Ri was slope position followed by D and Dom and, finally, Rh. These results provide an important basis for understanding the role of topography and tree social positions in solar radiation income in mountainous regions. Forest management measures should be varied with slope positions in mountainous regions, and forest density (i.e., distance between trees) should be considered as a key factor to optimize the forest functions.

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